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DBMS > AgensGraph vs. Apache Impala vs. EsgynDB vs. GraphDB

System Properties Comparison AgensGraph vs. Apache Impala vs. EsgynDB vs. GraphDB

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Editorial information provided by DB-Engines
NameAgensGraph  Xexclude from comparisonApache Impala  Xexclude from comparisonEsgynDB  Xexclude from comparisonGraphDB infoformer name: OWLIM  Xexclude from comparison
DescriptionMulti-model database supporting relational and graph data models and built upon PostgreSQLAnalytic DBMS for HadoopEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionEnterprise-ready RDF and graph database with efficient reasoning, cluster and external index synchronization support. It supports also SQL JDBC access to Knowledge Graph and GraphQL over SPARQL.
Primary database modelGraph DBMS
Relational DBMS
Relational DBMSRelational DBMSGraph DBMS
RDF store
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.17
Rank#320  Overall
#29  Graph DBMS
#143  Relational DBMS
Score10.63
Rank#40  Overall
#24  Relational DBMS
Score0.15
Rank#325  Overall
#144  Relational DBMS
Score2.76
Rank#99  Overall
#8  Graph DBMS
#4  RDF stores
Websitebitnine.net/­agensgraphimpala.apache.orgwww.esgyn.cnwww.ontotext.com
Technical documentationbitnine.net/­documentationimpala.apache.org/­impala-docs.htmlgraphdb.ontotext.com/­documentation
Social network pagesLinkedInTwitterYouTubeGitHubMedium
DeveloperBitnine Global Inc.Apache Software Foundation infoApache top-level project, originally developed by ClouderaEsgynOntotext
Initial release2016201320152000
Current release2.1, December 20184.1.0, June 202210.4, October 2023
License infoCommercial or Open SourceOpen Source infoApache License 2.0Open Source infoApache Version 2commercialcommercial infoSome plugins of GraphDB Workbench are open sourced
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCC++C++, JavaJava
Server operating systemsLinux
OS X
Windows
LinuxLinuxAll OS with a Java VM
Linux
OS X
Windows
Data schemedepending on used data modelyesyesschema-free and OWL/RDFS-schema support; RDF shapes
Typing infopredefined data types such as float or dateyesyesyesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nononono
Secondary indexesyesyesyesyes, supports real-time synchronization and indexing in SOLR/Elastic search/Lucene and GeoSPARQL geometry data indexes
SQL infoSupport of SQLyesSQL-like DML and DDL statementsyesstored SPARQL accessed as SQL using Apache Calcite through JDBC/ODBC
APIs and other access methodsCypher Query Language
JDBC
JDBC
ODBC
ADO.NET
JDBC
ODBC
GeoSPARQL
GraphQL
GraphQL Federation
Java API
JDBC
RDF4J API
RDFS
RIO
Sail API
Sesame REST HTTP Protocol
SPARQL 1.1
Supported programming languagesC
Java
JavaScript
Python
All languages supporting JDBC/ODBCAll languages supporting JDBC/ODBC/ADO.Net.Net
C#
Clojure
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresyesyes infouser defined functions and integration of map-reduceJava Stored Procedureswell-defined plugin interfaces; JavaScript server-side extensibility
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesno, but can be realized using table inheritanceShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication factorMulti-source replication between multi datacentersMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReduceyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate ConsistencyImmediate Consistency, Eventual consistency (configurable in cluster mode per master or individual client request)
Foreign keys infoReferential integrityyesnoyesyes infoConstraint checking
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standardDefault Basic authentication through RDF4J client, or via Java when run with cURL, default token-based in the Workbench or via Rest API, optional access through OpenID or Kerberos single sign-on.
More information provided by the system vendor
AgensGraphApache ImpalaEsgynDBGraphDB infoformer name: OWLIM
Specific characteristicsOntotext GraphDB is a semantic database engine that allows organizations to build...
» more
Competitive advantagesGraphDB allows you to link text and data in big knowledge graphs. It’s easy to experiment...
» more
Typical application scenariosMetadata enrichment and management, linked data publishing, semantic inferencing...
» more
Key customers​ GraphDB provides a platform for building next-generation AI and Knowledge Graph...
» more
Market metricsGraphDB is the most utilized semantic triplestore for mission-critical enterprise...
» more
Licensing and pricing modelsGraphDB Free is a non-commercial version and is free to use. GraphDB Enterprise edition...
» more
News

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Considerations to Creating a Graph Center of Excellence: 5 Elements to Ensure Success
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The Power of Knowledge Graphs – A Chat with Perfect Memory and Ontotext
16 August 2024

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
AgensGraphApache ImpalaEsgynDBGraphDB infoformer name: OWLIM
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